Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/11278
Title: A subpixel edge detector applied to aortic dissection detection
Authors: Trujillo-Pino, A. 
Krissian, Karl
Santana-Cedrés, D. 
Esclarín Monreal, Julio
Carreira-Villamor, José Martín
UNESCO Clasification: 220990 Tratamiento digital. Imágenes
Keywords: Aortic dissection
Subpixel edge detection
Anisotropic diffusion
Issue Date: 2012
Journal: Lecture Notes in Computer Science 
Abstract: The aortic dissection is a disease that can cause a deadly situation, even with a correct treatment. It consists in a rupture of a layer of the aortic artery wall, causing a blood flow inside this rupture, called dissection. The aim of this paper is to contribute to its diagnosis, detecting the dissection edges inside the aorta. A subpixel accuracy edge detector based on the hypothesis of partial volume effect is used, where the intensity of an edge pixel is the sum of the contribution of each color weighted by its relative area inside the pixel. The method uses a floating window centred on the edge pixel and computes the edge features. The accuracy of our method is evaluated on synthetic images of different hickness and noise levels, obtaining an edge detection with a maximal mean error lower than 16 percent of a pixel.
URI: http://hdl.handle.net/10553/11278
ISBN: 9783642275784
ISSN: 0302-9743
DOI: 10.1007/978-3-642-27579-1_28
Source: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)[ISSN 0302-9743],v. 6928 LNCS, p. 217-224
Rights: by-nc-nd
Appears in Collections:Actas de congresos
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